Neuromorphic Engineering Overview

Neuromorphic engineering, also known as neuromorphic computing, is a concept developed by Carver Mead, in the late 1980s, describing the use of very-large-scale integration (VLSI) systems containing electronic analog circuits to mimic neuro-biological architectures present in the nervous system.

In recent times the term neuromorphic has been used to describe analog, digital, and mixed-mode analog/digital VLSI and software systems that implement models of neural systems (for perception, motor control, or multisensory integration).

Big Neuron – Towards Big Data in Neuroscience

This year Hanchuan Peng (Allen Institute for Brain Science) began the next phase of the effort called Big Neuron. However, rather than a competition, this time the project would be a collaboration.

The key idea is to create a single platform on which all algorithms can be run, compared, and their results combined to form reconstructions better than any one could achieve alone.

Todd Gillette

Ph.D. in Neuroscience
Research Assistant in the Center for Neural Informatics, Neural Structures, and Neural Plasticity (CN3)
Curator of the Neuroscience Knowledge Network (NKN)

Doctoral Dissertation

My dissertation, entitled “Comparative topological analysis of neuronal arbors via sequence representation and alignment”, is focused on applying bioinformatic approaches to neuronal morphology to enable new discoveries and increase understanding about how morphology and neuron function interrelate.

Alignment and cluster analysis of neuronal tree sequences

Alignment of neurons represented as sequences of branching points can be used to detect clusters of similar neurons which can then be investigated for their stereotypical branching patterns. We use a modified sequence alignment procedure to produce pairwise similarity values between two neuronal sequences and then, after embedding the neurites (axons, dendrites, or apical dendrites) into a consistent abstract space, we found clusters in the space. By overlaying those clusters with known cell classes we found significant associations. There were strong associations by cell type, brain region, and species, indicating that neuronal branching patterns are indicative of neuronal type and function.

IBM’s TrueNorth – The first neuromorphic chip

IBM has recently released details of a neuromorphic chip named TrueNorth via their website, the press, and a research report in the journal Science. The research team, headed by Dharmendra Modha as part of the DARPA SyNAPSE Program, developed a chip containing a million “programmable spiking neurons” and 256 million synapses. The chips use 5.4 billion transistors on 4096 “neurosynaptic cores” which each has its memory (in the form of connection routing and timing delays) close to its “neuronal” processing units.

Mining Tree Patterns Poster

PDF of Poster

Neuronal morphology plays a major role in the electrophysiological and connectivity characteristics of neurons, and thus in neuron and network function.

Various morphometrics have been applied in studying neurons; however, the structural patterns of the tree-like dendrites and axons have yet to be fully explored. These patterns may reflect strategies that achieve functional properties such as dendritic compartmentalization, space filling, and targeting of various spatial distributions of synapses.

To address these issues we analyzed thousands of neurons, made available via NeuroMorpho.Org, in terms of structural patterns by representing their arbors (axons, dendrites, apical dendrites) as gene-like sequences. We compared neurons by arborization type within and between cell classes using sequence analysis techniques. Sequence domains can be used in conjunction with functional studies to further elucidate the structure-function relationship.


Gillette TA, Ascoli GA (2015) Topological characterization of neuronal arbor morphology via sequence representation: I – Motif analysis. BMC Bioinformatics, 16.
Summary | PDF

Gillette TA, Hosseini P, Ascoli GA (2015) Topological characterization of neuronal arbor morphology via sequence representation: II – Global alignmentBMC Bioinformatics, 16.
Summary | PDF

Polavaram S, Gillette TA, Parekh R, Ascoli GA (2014) Statistical analysis and data mining of digital reconstructions of dendritic morphologies. Frontiers in Neuroanatomy, 8:138.

Gillette TA, Brown KM, Ascoli GA (2011) The DIADEM Metric: Comparing multiple reconstructions of the same neuronNeuroinformatics, 9:233-45.

Gillette TA, Brown KM, Svoboda K, Liu Y, Ascoli GA (2011) DIADEMchallenge.Org: A compendium of resources fostering the contiuous development of automated neuronal reconstruction. Neuroinformatics, 9:2-3.

Gillette TA, Ascoli GA. Measuring and Modeling Morphology: How Dendrites Take Shape. In Le Novere N. (Ed.), “Computational Systems Neurobiology”, pp. 387-428, Springer (2012).

Theodore C Dumas, Todd A Gillette, Deveroux Ferguson et al. (2010) Anti-glucocorticoid gene therapy reverses the impairing effects of elevated corticosterone on spatial memory, hippocampal neuronal excitability, …

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